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Aude Billard

Cette personne a quitté l’EPFL

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Publications associées (258)

Page 3 sur 13

Synthesizing Robotic Handwriting Motion by Learning from Human Demonstrations

Aude Billard, Hang Yin

This paper contributes a novel framework that enables a robotic agent to efficiently learn and synthesize believable handwriting motion. We situate the framework as a foundation with the goal of allowing children to observe, correct and engage with the rob ...

2016

Statistical Learning by Imitation of Competing Constraints in Joint Space and Task Space

Aude Billard, Sylvain Calinon

We present a probabilistic architecture for solving generically the problem of extracting the task constraints through a Programming by Demonstration (PbD) framework and for generalizing the acquired knowledge to various situations. In previous work, we pr ...

2009

Roombots-Mechanical Design of Self-Reconfiguring Modular Robots for Adaptive Furniture

Pierre Dillenbourg, Auke Ijspeert, Aude Billard, Alexander Spröwitz

We aim at merging technologies from information technology, roomware, and robotics in order to design adaptive and intelligent furniture. This paper presents design principles for our modular robots, called Roombots, as future building blocks for furniture ...

2009

Pedestrian-Robot Interactions on Autonomous Crowd Navigation: Reactive Control Methods and Evaluation Metrics

Aude Billard, David Julian Gonon, Yujie He

Autonomous navigation in highly populated areas remains a challenging task for robots because of the difficulty in guaranteeing safe interactions with pedestrians in unstructured situations. In this work, we present a crowd navigation control framework tha ...

IEEE2022

On Force Synergies in Human Grasping Behavior

Aude Billard, Konstantinos Chatzilygeroudis

The human hand is a versatile and complex system with dexterous manipulation capabilities. For the transfer of human grasping capabilities to humanoid robotic and prosthetic hands, an understanding of the dynamic characteristics of grasp motions is fundame ...

IEEE2019

Learning search polices from humans in a partially observable context

Aude Billard, Guillaume Pierre Luc De Chambrier

Decision making and planning for which the state information is only partially available is a problem faced by all forms of intelligent entities they being either virtual, synthetic or biological. The standard approach to mathematically solve such a decisi ...

2014

Agent Prioritization and Virtual Drag Minimization in Dynamical System Modulation For Obstacle Avoidance of Decentralized Swarms

Alessandro Menichelli, Auke Ijspeert, Aude Billard, Lukas Huber, Anastasia Bolotnikova

Efficient and safe multi-agent swarm coordination in environments where humans operate, such as warehouses, assistive living rooms, or automated hospitals, is crucial for adopting automation. In this paper, we augment the obstacle avoidance algorithm based ...

IEEE2023

On Learning, Representing and Generalizing a Task in a Humanoid Robot

Aude Billard, Sylvain Calinon, Florent Günter

We present a Programming by Demonstration (PbD) framework for generically extracting the relevant features of a given task and for addressing the problem of generalizing the acquired knowledge to different contexts. We validate the architecture through a s ...

2007

Learning Motion Dynamics to Catch a Moving Object

Aude Billard, Elena Gribovskaya, Seungsu Kim

In this paper, we consider a novel approach to control the timing of motions when these are encoded with autonomous dynamical systems (DS). Accurate timing of motion is crucial if a robot must synchronize its movement with that of a fast moving object. In ...

2010

Learning collaborative manipulation tasks by demonstration using a haptic interface

Aude Billard, Sylvain Calinon, Elena Gribovskaya

This paper presents a method by which a robot can learn through observation to perform a collaborative manipulation task, namely lifting an object. The task is first demonstrated by a user controlling the robot's hand via a haptic interface. Learning extra ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2009

A Modular Approach to Learning Manipulation Strategies from Human Demonstration

Aude Billard, Miao Li, Ravin Luis De Souza

Object manipulation is a challenging task for robotics, as the physics involved in object interaction is com- plex and hard to express analytically. Here we introduce a modular approach for learning a manipulation strategy from human demonstration. Firstly ...

Springer Verlag2016

Credit Assignment Safety Learning from Human Demonstrations

Aude Billard, Ahalya Prabhakar

A critical need in assistive robotics, such as assistive wheelchairs for navigation, is a need to learn task intent and safety guarantees through user interactions in order to ensure safe task performance. For tasks where the objectives from the user are n ...

2021

Robots that share our spaces require proprioception and a sense of touch

Aude Billard

Imagine stepping away from your desk and reaching out for your office's light switch with your eyes closed. You might manage to complete the task successfully but might instead hit the corner of your desk or knock over the coffee mug your colleague just le ...

American Association for the Advancement of Science2025

The Ethical Landscape of Robotics

Aude Billard, Pawel Lichocki

This paper surveys some of the main ethical issues pertaining to robotics that have been discussed in the literature. We start with the idea of responsibility ascription that arises when an autonomous system malfunctions or harms people. Next, we discuss v ...

Institute of Electrical and Electronics Engineers2011

Hybrid Quadratic Programming - Pullback Bundle Dynamical Systems Control

Aude Billard, Bernardo Fichera

Dynamical System (DS)-based closed-loop control is a simple and effective way to generate reactive motion policies that well generalize to the robotic workspace, while retaining stability guarantees. Lately the formalism has been expanded in order to handl ...

SPRINGER INTERNATIONAL PUBLISHING AG2023

Coupled dynamical system based hand-arm grasp planning under real-time perturbations

Aude Billard, Ashwini Shukla

Robustness to perturbation has been advocated as a key element to robot control and efforts in that direction are numerous. While in essence these approaches aim at "endowing robots with a flexibility similar to that displayed by humans", few have actually ...

MIT Press2011

Efficient Configuration Exploration in Inverse Dynamics Acquisition of Robotic Manipulators

Sthithpragya Gupta, Aude Billard, Walid Amanhoud, Farshad Khadivar

The inverse dynamics of a robotic manipulator is instrumental in precise robot control and manipulation. However, acquiring such a model is challenging, not only due to unmodelled non-linearities such as joint friction, but also from a machine learning per ...

IEEE2021

Enhancing Dexterity in Confined Spaces: Real-Time Motion Planning for Multifingered In-Hand Manipulation

Aude Billard, Kunpeng Yao, Farshad Khadivar, Xiao Gao

Dexterous in-hand manipulation in robotics, particularly with multi-fingered robotic hands, poses significant challenges due to the intricate avoidance of collisions among fingers and the object being manipulated. Collision-free paths for all fingers must ...

2024

Hand pose selection in a bimanual fine-manipulation task

Aude Billard, Kunpeng Yao

Many daily tasks involve the collaboration of both hands. Humans dexterously adjust hand poses and modulate the forces exerted by fingers in response to task demands. Hand pose selection has been intensively studied in unimanual tasks, but little work has ...

2021

Transfer in Inverse Reinforcement Learning for Multiple Strategies

Aude Billard, Ajay Kumar Tanwani

We consider the problem of incrementally learning different strategies of performing a complex sequential task from multiple demonstrations of an expert or a set of experts. While the task is the same, each expert differs in his/her way of performing it. W ...

2013